PROJECT SUMMARY/ABSTRACT The majority (70.7%) of children aged 19?35 months are up-to-date on the recommended 7-vaccine series, but nearly 2,039,075 are under vaccinated and 57,237 have never received a vaccination. While data from the National Immunization Survey and other sources show that under- and unvaccinated children are more likely to live below the poverty line, the correlates of and solutions to reduce vaccination disparity are not well researched. We propose to advance the knowledge on vaccination disparities by addressing four aims: Aim 1?Identify which knowledge, attitudes, and beliefs (KAB), policy (e.g., Medicaid), access to vaccination services, quality of vaccination services, and other barriers contribute to vaccination disparities by poverty status. Aim 2?Assess whether these barriers vary by demographic subgroups (with a specific focus on race/ethnicity, census region, and urbanicity). Aim 3?Assess whether these barriers are consistent across variations of individuals who are not up-to- date (i.e., not at all vaccinated vs. under vaccinated). Aim 4?Develop policy, program, and funding recommendations that non-state entities, local, state, and federal agencies may adopt to reduce vaccination disparities by poverty status. To accomplish these aims, RTI, with Dr. Annika Hofstetter and four state Departments of Health (DOH), will use the Social Ecological Framework to collect, analyze, and translate data into policy, program, and funding recommendations. This conceptual framework recognizes an individual's behavior is influenced by external barriers occurring at various levels beyond the individual, including medical establishments and the community. Up-to-date status on a sample of children 19-35 months will be collected from participating state Immunization Information Systems (IIS). The parents/guardians of these children will be contacted to request participation in a survey about their own KAB, their child's insurance status, and other information. The IIS and survey data will be merged with publicly-available data on the neighborhood and community and information on state and local policies as provided by the DOHs. These data will be combined and analyzed using multi-level, multivariate models designed to account for the complex ways in which behaviors are influenced. Using the results of these models, in combination with relevant social and behavioral theory, the RTI team will develop a translation plan that federal, state, local, or nongovernmental agencies may use to develop policy and reduce the vaccination disparity among impoverished children.